Search results for " classification"
showing 10 items of 1043 documents
Determination of enzymatic activities using a miniaturized system as a rapid method to assess soil quality
2014
Summary Soil quality determination requires the analysis of a number of soil attributes using different approaches. In recent years, one of the most promising approaches has been the determination of enzymatic activities. Generally, only a few enzymes have been analysed and related to other soil properties such as total carbon, nitrogen content or microbial biomass carbon. The aim of this work was to investigate the possible use of the API ZYM strip, a semi-quantitative miniaturized system that determines 19 enzymatic activities, to study soil quality. To this end, we tested the system in different soil types, including albic Arenosols, mollic Leptosols, rendzic Leptosols, haplic Leptosols …
Premeditated automaticity : the role of explicit cognition in the development of obsessive smoking
2010
- Abstract The purpose of the present study was to examine the role of explicit cognitions in relation to the development of obsessive smoking passion. Data derives from a longitudinal internet survey conducted among 939 daily smokers over a period of four months. Mental representations were the strongest predictor of obsessive smoking passion (ß=.47, p<.001) followed by habit strength (ß=.25, p<.001) and number of cigarettes smoked (ß=.09, p<.01). Altogether the variables accounted for 48% of the variance in obsessive smoking passion. The results indicated that mental representations, along with automatic processes, play an important role in the prediction of obsessive smoking passion. The…
Dataset shift adaptation with active queries
2011
In remote sensing image classification, it is commonly assumed that the distribution of the classes is stable over the entire image. This way, training pixels labeled by photointerpretation are assumed to be representative of the whole image. However, differences in distribution of the classes throughout the image make this assumption weak and a model built on a single area may be suboptimal when applied to the rest of the image. In this paper, we investigate the use of active learning to correct the shifts that may appear when training and test data do not come from the same distribution. Experiments are carried out on a VHR remote sensing classification scenario showing that active learni…
Microaneurysm detection with radon transform-based classification on retina images.
2012
The creation of an automatic diabetic retinopathy screening system using retina cameras is currently receiving considerable interest in the medical imaging community. The detection of microaneurysms is a key element in this effort. In this work, we propose a new microaneurysms segmentation technique based on a novel application of the radon transform, which is able to identify these lesions without any previous knowledge of the retina morphological features and with minimal image preprocessing. The algorithm has been evaluated on the Retinopathy Online Challenge public dataset, and its performance compares with the best current techniques. The performance is particularly good at low false p…
Comparing Beerkan infiltration tests with rainfall simulation experiments for hydraulic characterization of a sandy-loam soil
2017
[EN] Saturated soil hydraulic conductivity, K-s, data collected by ponding infiltrometer methods and usual experimental procedures could be unusable for interpreting field hydrological processes and particularly rainfall infiltration. The K-s values determined by an infiltrometer experiment carried out by applying water at a relatively large distance from the soil surface could however be more appropriate to explain surface runoff generation phenomena during intense rainfall events. In this study, a link between rainfall simulation and ponding infiltrometer experiments was established for a sandy-loam soil. The height of water pouring for the infiltrometer run was chosen, establishing a sim…
Una revisión sistemática acerca del reconocimiento facial de las emociones en la Enfermedad de Alzheimer: una perspectiva evolutiva y de género
2021
La correcta identificación de las emociones básicas (alegría, miedo, asco, tristeza, sorpresa e ira) desempeñan un importante papel en las relaciones sociales y conductas ligadas a la propia supervivencia. En la Enfermedad de Alzheimer (EA) la capacidad de reconocimiento emocional podría estar ya alterada en fases iniciales. Por ello, el objetivo principal del presente trabajo fue realizar una revisión sistemática de la literatura acerca del reconocimiento facial en personas con EA, identificando posibles variables moduladoras. Se realizó una búsqueda en las bases de datos Web of Science y PsycINFO. Después de aplicar los criterios de inclusión-exclusión se seleccionaron un total de 28 artí…
“Anti-Bayesian” flat and hierarchical clustering using symmetric quantiloids
2017
A myriad of works has been published for achieving data clustering based on the Bayesian paradigm, where the clustering sometimes resorts to Naive-Bayes decisions. Within the domain of clustering, the Bayesian principle corresponds to assigning the unlabelled samples to the cluster whose mean (or centroid) is the closest. Recently, Oommen and his co-authors have proposed a novel, counter-intuitive and pioneering PR scheme that is radically opposed to the Bayesian principle. The rational for this paradigm, referred to as the “Anti-Bayesian” (AB) paradigm, involves classification based on the non-central quantiles of the distributions. The first-reported work to achieve clustering using the A…
A Neural Network model for the Evaluation of Text Complexity in Italian Language: a Representation Point of View
2018
Abstract The goal of a text simplification system (TS) is to create a new text suited to the characteristics of a reader, with the final goal of making it more understandable.The building of an Automatic Text Simplification System (ATS) cannot be separated from a correct evaluation of the text complexity. In fact the ATS must be capable of understanding if a text should be simplified for the target reader or not. In a previous work we have presented a model capable of classifying Italian sentences based on their complexity level. Our model is a Long Short Term Memory (LSTM) Neural Network capable of learning the features of easy-to-read and complex-to-read sentences autonomously from a anno…
Toward Self-Supervised Feature Learning for Online Diagnosis of Multiple Faults in Electric Powertrains
2021
This article proposes a novel online fault diagnosis scheme for industrial powertrains without using historical faulty or labeled training data. The proposed method combines a one-class support vector machine (SVM) based anomaly detection and supervised convolutional neural network (CNN) algorithms to online detect multiple faults and fault severities under variable speeds and loads. The one-class SVM algorithm is to derive a score for defining faults or health classes in the first stage, and the resulting health classes are used as the training data for the CNN-based classifier in the second stage. Within this framework, the self-supervised learning of the proposed CNN algorithm allows the…
Teacher satisfaction at the educational placement of students with special educational needs
2016
This study conducted a large-scale survey to investigate the satisfaction of Finnish primary school teachers toward the current educational placement of their students with special educational needs (SEN). Teachers were asked to recommend the most suitable educational placement for each of their SEN students from a pool of six alternatives: a mainstream classroom, part-time special education, a special classroom in the mainstream school, a special school, a state special school, or an institution. Data were obtained from 980 students representing 68 schools. The results showed that, in the majority of cases, teachers recommended a different level to the current level of placement for their …